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      Association between cannabis use and methadone maintenance treatment outcomes: an investigation into sex differences

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          Abstract

          Background

          Cannabis will soon become legalized in Canada, and it is currently unclear how this will impact public health. Methadone maintenance treatment (MMT) is the most common pharmacological treatment for opioid use disorder (OUD), and despite its documented effectiveness, a large number of patients respond poorly and experience relapse to illicit opioids. Some studies implicate cannabis use as a risk factor for poor MMT response. Although it is well established that substance-use behaviors differ by sex, few of these studies have considered sex as a potential moderator. The current study aims to investigate sex differences in the association between cannabis use and illicit opioid use in a cohort of MMT patients.

          Methods

          This multicentre study recruited participants on MMT for OUD from Canadian Addiction Treatment Centre sites in Ontario, Canada. Sex differences in the association between any cannabis use and illicit opioid use were investigated using multivariable logistic regression. A secondary analysis was conducted to investigate the association with heaviness of cannabis use.

          Results

          The study included 414 men and 363 women with OUD receiving MMT. Cannabis use was significantly associated with illicit opioid use in women only (OR = 1.82, 95% CI 1.18, 2.82, p = 0.007). Heaviness of cannabis use was not associated with illicit opioid use in men or women.

          Conclusions

          This is the largest study to date examining the association between cannabis use and illicit opioid use. Cannabis use may be a sex-specific predictor of poor response to MMT, such that women are more likely to use illicit opioids if they also use cannabis during treatment. Women may show improved treatment outcomes if cannabis use is addressed during MMT.

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          Most cited references 42

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          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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            A simulation study of the number of events per variable in logistic regression analysis.

            We performed a Monte Carlo study to evaluate the effect of the number of events per variable (EPV) analyzed in logistic regression analysis. The simulations were based on data from a cardiac trial of 673 patients in which 252 deaths occurred and seven variables were cogent predictors of mortality; the number of events per predictive variable was (252/7 =) 36 for the full sample. For the simulations, at values of EPV = 2, 5, 10, 15, 20, and 25, we randomly generated 500 samples of the 673 patients, chosen with replacement, according to a logistic model derived from the full sample. Simulation results for the regression coefficients for each variable in each group of 500 samples were compared for bias, precision, and significance testing against the results of the model fitted to the original sample. For EPV values of 10 or greater, no major problems occurred. For EPV values less than 10, however, the regression coefficients were biased in both positive and negative directions; the large sample variance estimates from the logistic model both overestimated and underestimated the sample variance of the regression coefficients; the 90% confidence limits about the estimated values did not have proper coverage; the Wald statistic was conservative under the null hypothesis; and paradoxical associations (significance in the wrong direction) were increased. Although other factors (such as the total number of events, or sample size) may influence the validity of the logistic model, our findings indicate that low EPV can lead to major problems.
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              Adverse Health Effects of Marijuana Use

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                Author and article information

                Contributors
                zielinsl@mcmaster.ca
                bhattm25@mcmaster.ca
                sangern@mcmaster.ca
                counselling@carolynplater.ca
                worster@mcmaster.ca
                mvarenbut@canatc.ca
                jdaiter@canatc.ca
                pareg@mcmaster.ca
                david.marsh@nosm.ca
                dipika.desai@phri.ca
                jmackill@mcmaster.ca
                mst@mcmaster.ca
                smcdermi@stjosham.on.ca
                thabanl@mcmaster.ca
                905 522 1155 , samaanz@mcmaster.ca
                Journal
                Biol Sex Differ
                Biol Sex Differ
                Biology of Sex Differences
                BioMed Central (London )
                2042-6410
                30 March 2017
                30 March 2017
                2017
                : 8
                Affiliations
                [1 ]ISNI 0000 0004 1936 8227, GRID grid.25073.33, MiNDS Neuroscience Graduate Program, , McMaster University, ; Hamilton, ON Canada
                [2 ]ISNI 0000 0004 1936 8227, GRID grid.25073.33, Health Research Methodology Graduate Program, , McMaster University, ; Hamilton, ON Canada
                [3 ]ISNI 0000 0004 1936 8227, GRID grid.25073.33, Medical Science Graduate Program, , McMaster University, ; Hamilton, ON Canada
                [4 ]Canadian Addiction Treatment Centres, Hamilton, ON Canada
                [5 ]ISNI 0000 0004 1936 8227, GRID grid.25073.33, Department of Medicine, , McMaster University, ; Hamilton, ON Canada
                [6 ]ISNI 0000 0004 1936 8227, GRID grid.25073.33, Population Genomics Program, Chanchlani Research Centre, , McMaster University, ; Hamilton, ON Canada
                [7 ]ISNI 0000 0004 1936 8227, GRID grid.25073.33, Department of Clinical Epidemiology and Biostatistics, , McMaster University, ; Hamilton, ON Canada
                [8 ]ISNI 0000 0000 8658 0974, GRID grid.436533.4, , Northern Ontario School of Medicine, ; Sudbury, ON Canada
                [9 ]ISNI 0000 0004 1936 8227, GRID grid.25073.33, Department of Psychiatry and Behavioural Neurosciences, , McMaster University, ; Hamilton, ON Canada
                [10 ]ISNI 0000 0001 0742 7355, GRID grid.416721.7, , Peter Boris Centre for Addictions Research, St. Joseph’s Healthcare Hamilton, ; Hamilton, ON Canada
                [11 ]ISNI 0000 0001 0742 7355, GRID grid.416721.7, Women’s Health Concerns Clinic, , St. Joseph’s Healthcare Hamilton, ; Hamilton, ON Canada
                [12 ]ISNI 0000 0004 1936 8227, GRID grid.25073.33, Department of Obstetrics and Gynaecology, , McMaster University, ; Hamilton, ON Canada
                [13 ]ISNI 0000 0001 0742 7355, GRID grid.416721.7, Cleghorn Early Intervention Clinic, , St. Joseph’s Healthcare Hamilton, ; Hamilton, ON Canada
                [14 ]ISNI 0000 0001 0742 7355, GRID grid.416721.7, Biostatistics Unit, Research Institute at St Joes, , St. Joseph’s Healthcare Hamilton, ; Hamilton, ON Canada
                Article
                130
                10.1186/s13293-017-0130-1
                5372283
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Funding
                Funded by: CIHR Drug Safety and Effectiveness Network
                Award ID: 126639
                Award Recipient :
                Funded by: Peter Boris Centre for Addictions Research
                Funded by: Chanchlani Research Centre
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                Human biology

                sex differences, opioid use disorder, opioid, cannabis, methadone maintenance treatment

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